Urban mobility faces growing challenges due to the inefficiencies of traditional public transportation systems, which rely on fixed schedules and routes. These systems struggle to meet dynamic passenger demands, resulting in overcrowding during peak times and underutilization during off-peak periods. Variable passenger demand frequently results in inefficiencies in public transportation networks, which create crowding during rush hours and underutilization during off-peak hours. The proposed system offers a Smart Ticket Scheduling System that uses real-time crowd data to dynamically schedule and distribute tickets in order to overcome these difficulties. Using sensors, cameras, and mobile network data, the system tracks the number of passengers at different locations by utilizing technologies like IoT, AI, and advanced analytics. By controlling ticket availability and managing passenger flow, this data ensures that commuters are distributed among buses and other public transportation options as efficiently as possible. Additionally, the technology modifies bus routes and schedules in real-time to meet changes in demand, which eases traffic and enhances the entire travel experience.


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    Titel :

    Real Time Adaptive Routing for Efficient Urban Mobility


    Beteiligte:
    Karthika, I. (Autor:in) / Pushpalatha, D. (Autor:in) / D, Infant Hilda (Autor:in) / S, Dheenadhayalan (Autor:in) / K, Mukilan (Autor:in) / S, Hariprasaath (Autor:in)


    Erscheinungsdatum :

    04.03.2025


    Format / Umfang :

    805580 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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